Player tracking, ball detection, event recognition, and performance analytics annotation for sports AI and broadcast intelligence.
Event hierarchies defined per sport — action types (pass, shot, tackle, foul), player roles, formation patterns, and game state (possession, set piece, transition). Rules-aware annotation guidelines prevent logically inconsistent labels.
Broadcast feeds and stadium cameras temporally aligned. Camera handoff zones mapped for continuous player tracking across views. Slow-motion replays linked to real-time timestamps.
Per-frame player detection with jersey number OCR, team assignment, and persistent track IDs. Pose estimation keypoints (17-point COCO skeleton) for biomechanical analysis.
Temporal event boundaries labeled with action type, involved players, outcome (success/fail), and spatial location on field/court coordinate system.
Team formations classified at configurable intervals (e.g., every 5 seconds). Player positioning mapped to standardized coordinate systems for tactical analysis.
Labels delivered in sport-specific formats with frame-accurate timestamps, court/field coordinate mappings, and real-time streaming compatibility for live broadcast integration.
Generic annotation vendors can label data. Domain experts label it correctly. Here's why the difference matters in your industry.
A "handball" in soccer has different rules in the penalty area vs. midfield. An "offside" requires understanding of the last defender's position. Our annotators undergo sport-specific rules training — ensuring event labels are logically consistent with game rules.
22 players on a soccer pitch create constant occlusions. Our annotators maintain persistent track IDs through occlusion using jersey numbers, player appearance, and spatial continuity — achieving 96%+ tracking accuracy where generic trackers fail at 80-85%.
Live broadcast graphics overlay depends on frame-accurate annotations. Our labels are timestamped to individual frames with broadcast timecode synchronization — enabling real-time stats overlays and instant replay analysis.
See how our domain-specific capabilities compare to generic annotation services.
| Capability | UTL Data Engine | Typical Vendor |
|---|---|---|
| Sport-specific event taxonomies (rules-aware) | 15+ sports | Generic action detection |
| Jersey number OCR + team assignment | Per-frame | Manual or missing |
| Tactical formation classification | Configurable intervals | Not available |
| Multi-camera player tracking with handoff | Cross-view linked | Single-camera |
| Field/court coordinate mapping | Standardized | Pixel coordinates |
| Pose estimation (17-point keypoints) | COCO skeleton | Bounding box only |
"Sports annotation requires understanding the game. UTL's team knew the difference between a screen and a pick — that domain knowledge made all the difference."
Let's discuss your specific data challenges and build a tailored annotation pipeline.
